kb-anonymity: A model for anonymized behavior-preserving test and debugging data
It is often very expensive and practically infeasible to generate test cases that can exercise all possible program states in a program. This is especially true for a medium or large industrial system. In practice, industrial clients of the system often have a set of input data collected either befo...
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sg-smu-ink.sis_research-23892017-02-04T10:07:54Z kb-anonymity: A model for anonymized behavior-preserving test and debugging data BUDI, Aditya LO, David JIANG, Lingxiao Lucia, Lucia It is often very expensive and practically infeasible to generate test cases that can exercise all possible program states in a program. This is especially true for a medium or large industrial system. In practice, industrial clients of the system often have a set of input data collected either before the system is built or after the deployment of a previous version of the system. Such data are highly valuable as they represent the operations that matter in a client's daily business and may be used to extensively test the system. However, such data often carries sensitive information and cannot be released to third-party development houses. For example, a healthcare provider may have a set of patient records that are strictly confidential and cannot be used by any third party. Simply masking sensitive values alone may not be sufficient, as the correlation among fields in the data can reveal the masked information. Also, masked data may exhibit different behavior in the system and become less useful than the original data for testing and debugging.For the purpose of releasing private data for testing and debugging, this paper proposes the kb-anonymity model, which combines the k-anonymity model commonly used in the data mining and database areas with the concept of program behavior preservation. Like k-anonymity, kb-anonymity replaces some information in the original data to ensure privacy preservation so that the replaced data can be released to third-party developers. Unlike k-anonymity, kb-anonymity ensures that the replaced data exhibits the same kind of program behavior exhibited by the original data so that the replaced data may still be useful for the purposes of testing and debugging. We also provide a concrete version of the model under three particular configurations and have successfully applied our prototype implementation to three open source programs, demonstrating the utility and scalability of our prototype. 2011-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1390 info:doi/10.1145/1993316.1993551 https://ink.library.smu.edu.sg/context/sis_research/article/2389/viewcontent/kbAnonymity_PLDI2011.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University k-anonymity symbolic execution third-party testing and debugging behavior preservation Software Engineering |
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k-anonymity symbolic execution third-party testing and debugging behavior preservation Software Engineering BUDI, Aditya LO, David JIANG, Lingxiao Lucia, Lucia kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
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It is often very expensive and practically infeasible to generate test cases that can exercise all possible program states in a program. This is especially true for a medium or large industrial system. In practice, industrial clients of the system often have a set of input data collected either before the system is built or after the deployment of a previous version of the system. Such data are highly valuable as they represent the operations that matter in a client's daily business and may be used to extensively test the system. However, such data often carries sensitive information and cannot be released to third-party development houses. For example, a healthcare provider may have a set of patient records that are strictly confidential and cannot be used by any third party. Simply masking sensitive values alone may not be sufficient, as the correlation among fields in the data can reveal the masked information. Also, masked data may exhibit different behavior in the system and become less useful than the original data for testing and debugging.For the purpose of releasing private data for testing and debugging, this paper proposes the kb-anonymity model, which combines the k-anonymity model commonly used in the data mining and database areas with the concept of program behavior preservation. Like k-anonymity, kb-anonymity replaces some information in the original data to ensure privacy preservation so that the replaced data can be released to third-party developers. Unlike k-anonymity, kb-anonymity ensures that the replaced data exhibits the same kind of program behavior exhibited by the original data so that the replaced data may still be useful for the purposes of testing and debugging. We also provide a concrete version of the model under three particular configurations and have successfully applied our prototype implementation to three open source programs, demonstrating the utility and scalability of our prototype. |
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BUDI, Aditya LO, David JIANG, Lingxiao Lucia, Lucia |
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BUDI, Aditya LO, David JIANG, Lingxiao Lucia, Lucia |
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BUDI, Aditya |
title |
kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
title_short |
kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
title_full |
kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
title_fullStr |
kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
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kb-anonymity: A model for anonymized behavior-preserving test and debugging data |
title_sort |
kb-anonymity: a model for anonymized behavior-preserving test and debugging data |
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Institutional Knowledge at Singapore Management University |
publishDate |
2011 |
url |
https://ink.library.smu.edu.sg/sis_research/1390 https://ink.library.smu.edu.sg/context/sis_research/article/2389/viewcontent/kbAnonymity_PLDI2011.pdf |
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